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MCP-native procurement decision infrastructure

Put procurement judgement inside your AI.

Brisora turns procurement evidence, commercial policy and uncertainty into deterministic decisions with provenance.

The AI handles the conversation. Brisora determines what the evidence supports.

Deterministic evaluation Evidence with exact sources Unknown stays unknown Policy-controlled Human authority preserved

What Brisora is.

Brisora is an evidence-bound procurement decision engine. It is built to be used from the AI client your team already works in, through MCP, so that client can ask it to qualify a public tender, evaluate a commercial action against a mandate, calculate landed cost or compare sourcing options.

An AI model can explain a procurement decision fluently and still be wrong about what the documents say. Brisora exists so the decision does not depend on the explanation: every outcome comes from fixed rules over explicit evidence, and carries the trace needed to check it.

Who it is for

Teams whose procurement decisions have to survive scrutiny.

Bid and tender teams

Deciding which public tenders deserve sourcing effort, with the missing facts named rather than guessed.

Sourcing and commercial teams

Comparing supplier and bill-of-materials options on worst-case economics, not on an optimistic estimate.

Teams building AI agents

Giving an agent procurement judgement it can call, without letting the agent make the judgement itself.

Where to go next

One topic per page.

Access

Brisora MCP

How an AI client calls Brisora, the four tools it exposes, and what the server cannot do.

What Brisora MCP is →
Capability

Tender intelligence

Qualifying a public tender notice from its own evidence, with missing and ambiguous facts kept explicit.

How tender qualification works →
Capability

Commercial analysis

Landed cost, margin, sourcing comparison and commercial-policy evaluation against a mandate.

How commercial analysis works →
Differentiator

Decision provenance

The chain from source to outcome that lets an AI-generated explanation be checked.

What decision provenance is →
Technical

Architecture

Where the conversation layer ends and the decision engine begins.

How the system is built →
Trust

Principles

Five rules the engine enforces, each stated as concrete behavior.

The rules Brisora enforces →

For the whole decision chain in one place, start with the product overview.

See it on a decision you care about.

Brisora MCP is being opened through a private demo program, on public and synthetic data.